# Staff + Senior Software Engineer, Inference Deployment

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY, Seattle, WA
**Role:** ML Engineering
**Salary:** $320k – $485k/yr
**Experience:** 7+ years
**Skills:** Distributed Systems, Kubernetes, Python, Rust, AWS, GCP, Azure, load balancing, request routing, llm inference, machine learning systems
**Posted:** 2026-07-14

> Build and maintain large-scale distributed inference systems serving Claude to millions of users. Design intelligent routing, autoscaling, and deployment pipelines across diverse AI accelerators while maximizing compute efficiency for production and research workloads. Requires significant distributed systems experience.

## Job Description

## Key Responsibilities
- Design, build, and maintain the distributed systems that serve Claude to millions of users worldwide.
- Develop resilient, flexible systems that adapt in real time to real world events.
- Develop intelligent request routing, load balancing, and traffic management systems across thousands of accelerators.
- Maximize compute efficiency across the fleet by autoscaling and orchestrating production, research, and experimental workloads.
- Build and operate production-grade deployment pipelines for releasing new models to users.
- Provide high-performance inference infrastructure that enables researchers to develop next-generation models.
- Integrate new AI accelerator platforms and support inference for new model architectures.

## Minimum Qualifications
- Significant software engineering experience, particularly with distributed systems.
- Results-oriented, with a bias towards flexibility and impact.
- Willingness to pick up slack, even if it goes outside your job description.
- Desire to learn more about machine learning systems and infrastructure.
- Thrive in environments where technical excellence directly drives both business results and research breakthroughs.
- Care about the societal impacts of your work.

## Preferred Qualifications
- Experience with high-performance, large-scale distributed systems.
- Experience implementing and deploying machine learning systems at scale.
- Experience with load balancing, request routing, or traffic management systems.
- Familiarity with LLM inference optimization, batching, and caching strategies.
- Experience with Kubernetes and cloud infrastructure (AWS, GCP, Azure).
- Proficiency in Python or Rust.

## Representative Projects
- Designing intelligent routing algorithms that optimize request distribution across many accelerators in different environments.
- Autoscaling our compute fleet to dynamically match supply with demand across production, research, and experimental workloads.
- Building production-grade deployment pipelines for releasing new models to millions of users reliably.
- Contributing to new inference features.
- Supporting inference for new model architectures.
- Analyzing observability data to tune performance based on real-world production workloads.
- Managing multi-region deployments and geographic routing for global customers.

## Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience in a field relevant to the role.

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